[HTML][HTML] Artificial intelligence and smart vision for building and construction 4.0: Machine and deep learning methods and applications
This article presents a state-of-the-art review of the applications of Artificial Intelligence (AI),
Machine Learning (ML), and Deep Learning (DL) in building and construction industry 4.0 in …
Machine Learning (ML), and Deep Learning (DL) in building and construction industry 4.0 in …
[HTML][HTML] A comprehensive overview of jute fiber reinforced cementitious composites
H Song, J Liu, K He, W Ahmad - Case Studies in Construction Materials, 2021 - Elsevier
Natural fibers are eco-friendly, cost-effective, lightweight, renewable, have better thermal
properties and corrosion resistance capabilities. The addition of natural fibers in …
properties and corrosion resistance capabilities. The addition of natural fibers in …
Machine learning techniques and multi-scale models to evaluate the impact of silicon dioxide (SiO2) and calcium oxide (CaO) in fly ash on the compressive strength of …
Fly ash is a by-product almost found in coal power plants; it is available worldwide.
According to the hazardous impacts of cement on the environment, fly ash is known to be a …
According to the hazardous impacts of cement on the environment, fly ash is known to be a …
[HTML][HTML] Predicting the compressive strength of concrete with fly ash admixture using machine learning algorithms
The cementitious composites have different properties in the changing environment. Thus,
knowing their mechanical properties is very important for safety reasons. The most important …
knowing their mechanical properties is very important for safety reasons. The most important …
Prediction model for rice husk ash concrete using AI approach: Boosting and bagging algorithms
The use of rice husk ash (RHA) in concrete serves a positive role. The compressive strength
of RHA in concrete is predicted using supervised machine learning approaches such as …
of RHA in concrete is predicted using supervised machine learning approaches such as …
Comparative study of supervised machine learning algorithms for predicting the compressive strength of concrete at high temperature
High temperature severely affects the nature of the ingredients used to produce concrete,
which in turn reduces the strength properties of the concrete. It is a difficult and time …
which in turn reduces the strength properties of the concrete. It is a difficult and time …
Predictive modeling of mechanical properties of silica fume-based green concrete using artificial intelligence approaches: MLPNN, ANFIS, and GEP
Silica fume (SF) is a mineral additive that is widely used in the construction industry when
producing sustainable concrete. The integration of SF in concrete as a partial replacement …
producing sustainable concrete. The integration of SF in concrete as a partial replacement …
Compressive strength prediction via gene expression programming (GEP) and artificial neural network (ANN) for concrete containing RCA
To minimize the environmental risks and for sustainable development, the utilization of
recycled aggregate (RA) is gaining popularity all over the world. The use of recycled coarse …
recycled aggregate (RA) is gaining popularity all over the world. The use of recycled coarse …
Artificial-intelligence-led revolution of construction materials: From molecules to Industry 4.0
Industry 4.0 promotes the transformation of manufacturing industry to intelligence, which
demands advances in materials, devices, and systems of the construction industry …
demands advances in materials, devices, and systems of the construction industry …
[HTML][HTML] Machine learning interpretable-prediction models to evaluate the slump and strength of fly ash-based geopolymer
This study used three artificial intelligence-based algorithms–adaptive neuro-fuzzy inference
system (ANFIS), artificial neural networks (ANNs), and gene expression programming (GEP) …
system (ANFIS), artificial neural networks (ANNs), and gene expression programming (GEP) …